Advanced Driver Assistance Systems (ADAS) were developed to improve the comfort, efficiency, safety, and overall satisfaction of driving. Examples of these advanced driver assistance systems include adaptive headlight aiming, adaptive cruise control, lane departure warning and control, curve warning, speed limit notification, hazard warning, predictive cruise control, adaptive shift control, as well as others. Some of these advanced driver assistance systems use a variety of sensor mechanisms in the vehicle to determine the current state of the vehicle and the current state of the roadway in front of the vehicle. These sensor mechanisms may include radar, infrared, ultrasonic, and vision-oriented sensors, such as digital video cameras and LIDAR.
Some advanced driver assistance systems also use digital map data. These systems are sometimes referred to as map-enhanced ADAS. The digital map data can be used in advanced driver assistance systems to provide information about the road network, road geometry, road conditions, and other items associated with the road and terrain around the vehicle. Unlike some sensors, the digital map data is not affected by environmental conditions, such as fog, rain, or snow. In addition, the digital map data can provide useful information that cannot reliably be provided by sensors, such as curvature, grade, bank, speed limits that are not indicated by signage, lane restrictions, and so on. Further, digital map data can provide a predictive capability well beyond the range of sensors or even beyond the driver's vision to determine the road ahead of the vehicle, around corners, over hills, or beyond obstructions. Accordingly, the digital map data can be a useful addition for some advanced driver assistance systems.
The map-enhanced advanced driver assistance systems commonly use data from a geographic database associated with a navigation system in a vehicle. The navigation system database contains data that represents the road network in the region, such as the locations (geographic coordinates, including altitude) of roads and intersections, road names, speed limits along roads, turn restrictions at intersections, addresses or address ranges along roads, the number of lanes for each road, lane width, lane markings, functional classes of roads, the locations of medians, and so on. The navigation system database may also contain information about other geographic features, such as bodies of water, parks, administrative areas (including municipal, state, and country boundaries), and locations of points of interest, such as businesses, hospitals, police stations, and so on.
In some geographic databases, each road is represented as one or more discrete road segments, each of which is represented by a separate data entity. A representation of a road segment includes, among other things, information about its location (i.e., latitude, longitude, and possibly altitude) and shape. If a road segment is straight, it can be represented by identifying its endpoints. However, if a road is other-than-straight, additional information is required to indicate the shape of the road.
One way to represent the shape of a curved road segment, is to use shape points. Shape points are points through which a road segment passes between its end points. By providing the coordinates of one or more shape points, the shape of a curved road segment can be represented.
There are other ways of representing other-than-straight linearly extending features. For example, linearly extending features may be represented using mathematical expressions, such as splines. The use of mathematical expressions may provide for a smooth and possibly more realistic way to represent linearly extending geographic features.
Although use of mathematical expressions provides advantages, there is still room for improvement. For example, when modeling road geometry it may not be possible to model all aspects of the road with a single curve. For example, with road center geometry and lane paint stripe geometry it may not possible to satisfy both geometry position constraints and curvature constraints simultaneously with a single curve. Road center geometry needs to be smooth to represent fair curvature and, therefore, sacrifices precision to maintain curvature and heading smoothness. On the other hand, lane paint stripe geometry has very high precision and, therefore, has noisy curvature. The same holds true for 3D road height and slope.
U.S. Pat. No. 7,477,988, assigned to the same assignee as the current application and hereby incorporated by reference, describes a dual road geometry representation that supports ADAS. One road geometry data representation indicates the road position, e.g., road centerline or lane centerline, and the other road geometry data representation indicates the road shape, e.g., curvature and/or heading. However, it would be beneficial to have a single curve representation to simplify the road data model.